Optimal Selection of the Regularization Parameter for pyGIMLi: Geophysical Inversion and Modeling Library

Despite the major contributions made over recent years in the computing field to solve inverse problems in geophysics and related areas, there are internal aspects in the proposed methodologies that should be studied and analyzed to make progress in the continued improvement of such developments. This work includes a conceptual explanation of the pyGIMLi library inversion model that has the purpose of determining, through an estimation algorithm, the optimal values for the computational execution of the inverse problem because non of the currently available tools provide this parameter. In addition, the algorithm is verified by using data supplied by the library, as well as an analysis of the results obtained through the proposed computational methodology.